Improving Parametric Mortgage Prepayment Models with Non-parametric Kernel Regression

Michael LaCour-Little, Michael Marschoun and Clark Maxam

Journal of Real Estate Research, 2002, vol. 24, issue 3, 299-328

Abstract: Developing a good prepayment model is a central task in the valuation of mortgages and mortgage-backed securities but conventional parametric models often have bad out-of-sample predictive ability. A likely explanation is the highly non-linear nature of the prepayment function. Non-parametric techniques are much better at detecting non-linearity and multivariate interaction. This article discusses how non-parametric kernel regression may be applied to loan level event histories to produce a better parametric model. By utilizing a parsimonious specification, a model can be produced that practitioners can use in valuation routines based on Monte Carlo interest rate simulation.

Date: 2002
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DOI: 10.1080/10835547.2002.12091098

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